Protein-protein interactions as a target for drugs in proteomics

Protein-protein interactions play a central role in numerous processes in the cell and are one of the main fields of functional proteomics. This review highlights the methods of bioinformatics and functional proteomics of protein-protein interaction investigation. The structures and properties of contact surfaces, forces involved in protein-protein interactions, kinetic and thermodynamic parameters of these reactions were considered. The properties of protein contact surfaces depend on their functions. The contact surfaces of permanent complexes resemble domain contacts or the protein core and it is reasonable to consider such complex formation as a continuation of protein folding. Characteristics of contact surfaces of temporary protein complexes share some similarities with active sites of enzymes. The contact surfaces of the temporary protein complexes have unique structure and properties and they are more conservative in comparison with active site of enzymes. So they represent prospective targets for a new generation of drugs. During the last decade, numerous investigations were undertaken to find or design small molecules that block protein dimerization or protein(peptide)-receptor interaction, or, on the contrary, to induce protein dimerization.     

Small-world network approach to identify key residues in protein-protein interaction

We show that protein complexes can be represented as small-world networks, exhibiting a relatively small number of highly central amino-acid residues occurring frequently at protein-protein interfaces. We further base our analysis on a set of different biological examples of protein-protein interactions with experimentally validated hot spots, and show that 83% of these predicted highly central residues, which are conserved in sequence alignments and nonexposed to the solvent in the protein complex, correspond to or are in direct contact with an experimentally annotated hot spot. The remaining 17% show a general tendency to be close to an annotated hot spot. On the other hand, although there is no available experimental information on their contribution to the binding free energy, detailed analysis of their properties shows that they are good candidates for being hot spots. Thus, highly central residues have a clear tendency to be located in regions that include hot spots. We also show that some of the central residues in the protein complex interfaces are central in the monomeric structures before dimerization and that possible information relating to hot spots of binding free energy could be obtained from the unbound structures.     

Selected peptide extension contacts hydrophobic patch on neighboring zinc finger and mediates dimerization on DNA.

Protein-protein interactions often play a crucial role in stabilizing protein-DNA complexes and thus facilitate site-specific DNA recognition. We have worked to incorporate such protein-protein contacts into our design and selection strategies for short peptide extensions that promote cooperative binding of zinc finger proteins to DNA. We have determined the crystal structure of one of these fusion protein-DNA complexes. The selected peptide extension was found to mediate dimerization by reaching across the dyad axis and contacting a hydrophobic patch on the surface of the zinc finger bound to the adjacent DNA site. The peptide-zinc finger protein interactions observed in this structure are similar to those of some homeodomain heterodimers. We also find that the region of the zinc finger surface contacted by the selected peptide extension corresponds to surfaces that also make key interactions in the zinc finger proteins GLI and SWI5.     

Potential of mean force for protein-protein interaction studies.

Calculating protein-protein interaction energies is crucial for understanding protein-protein associations. On the basis of the methodology of mean-field potential, we have developed an empirical approach to estimate binding free energy for protein-protein interactions. This knowledge-based approach has been used to derive distance-dependent free energies of protein complexes from a nonredundant training set in the Protein Data Bank (PDB), with a careful treatment of homology. We calculate atom pair potentials for 16 pair interactions, which can reflect the importance of hydrophobic interactions and specific hydrogen-bonding interactions. The derived potentials for hydrogen-bonding interactions show a valley of favorable interactions at a distance of approximately 3 A, corresponding to that of an established hydrogen bond. For the test set of 28 protein complexes, the calculated energies have a correlation coefficient of 0.75 compared with experimental binding free energies. The performance of the method in ranking the binding energies of different protein-protein complexes shows that the energy estimation can be applied to value binding free energies for protein-protein associations.     

Does structural and chemical divergence play a role in precluding undesirable protein interactions?

To understand the evolutionary forces establishing, maintaining, breaking, or precluding protein-protein interactions, a comprehensive data set of protein complexes has been analyzed to examine the overlap between protein interfaces and the most conserved or divergent protein surface areas. The most divergent areas tend to be found predominantly away from protein interfaces, although when found at interfaces, they are associated with specific lack of cross-reactivity between close homologues, like in antibody-antigen complexes. Moreover, the amino acid composition of highly variable regions is significantly different from any other protein surfaces. The variable regions present higher structural plasticity as a result of insertions and deletions, and favor charged over hydrophobic residues, a known strategy to minimize aggregation. This suggests that (1) a rapid rate of mutations at these regions might be continuously altering their properties, making difficult the coadaptation, in shape and chemical complementarity, to potential interacting partners; and (2) the existence of some form of selective pressure for variable areas away from interfaces to accumulate charged residues, perhaps as an evolutionary mechanism to increase solubility and minimize undesirable interactions within the crowded cellular environment. Finally, these results are placed into the context of the aberrant oligomerization of sickle-cell anemia hemoglobin and prion proteins.     

Stalking metal-linked dimers

Protein dimerization is essential for cellular processes including regulation and biosignalling. While protein-protein interactions can occur through many modes, this review will focus on those interactions mediated through the binding of metal ions to the proteins. Selected techniques used to study protein-protein interactions, including size exclusion chromatography, mass spectrometry, affinity chromatography, and frontal zone chromatography, are described as applied to the characterization of the Enterococcus hirae protein CopY. CopY forms a homodimer to control the expression of proteins involved in the homeostasis of cellular copper levels. At the center of the CopY dimerization interaction lies a metal binding motif, -CxCxxxxCxC-, capable of binding Zn(II) or Cu(I). The binding of metal to this cysteine hook motif, one within each monomer, is critical to the dimerization interaction. The CopY dimer is also stabilized by hydrophobic interactions between the two monomers. The cysteine hook metal binding motif has been identified in numerous other uncharacterized proteins across the biological spectrum. The prevalence of the motif gives evidence to the biological relevance of this motif, both as a metal binding domain and as a dimerization motif.     

Stability of macromolecular complexes

Macromolecular interactions are crucial in numerous biologic processes, yet few general principles are available that establish firm expectations for the strength of these interactions or the expected contribution of specific forces. The simplest principle would be a monotonic increase in interactions as the size of the interface grows. The exact relationship might be linear or nonlinear depending on the nature of the forces involved. Simple "linear-free energy" relationships based on atomic properties have been well documented, for example, additivity for the interaction of small molecules with solvent, and, recently, have been explored for ligand-receptor interactions. Horton and Lewis propose such additivity based on buried surface area for protein-protein complexes. We investigated macromolecular interactions and found that the highest-affinity complexes do not fulfill this simple expectation. Instead, binding free energies of the tightest macromolecular complexes are roughly constant, independent of interface size, with the notable exception of DNA duplexes. By comparing these results to an earlier study of protein-ligand interactions we find that: (1) The maximum affinity is approximately 1.5 kcal/mol per nonhydrogen atom or 120 cal/mol A(2) of buried surface area, comparable to results of our earlier work; (2) the lack of an increase in affinity with interface size is likely due to nonthermodynamic factors, such as functional and evolutionary constraints rather than some fundamental physical limitation. The implication of these results have some importance for molecular design because they suggest that: (1) The stability of any given complex can be increased significantly if desired; (2) small molecule inhibitors of macromolecular interactions are feasible; and (3) different functional classes of protein-protein complexes exhibit differences in maximal stability, perhaps in response to differing evolutionary pressures. These results are consistent with the widespread observation that proteins have not evolved to maximize thermodynamic stability, but are only marginally stable.     

Protein-protein complexation in bioluminescence

In this review we summarize the progress made towards understanding the role of protein-protein interactions in the function of various bioluminescence systems of marine organisms, including bacteria, jellyfish and soft corals, with particular focus on methodology used to detect and characterize these interactions. In some bioluminescence systems, protein-protein interactions involve an “accessory protein” whereby a stored substrate is efficiently delivered to the bioluminescent enzyme luciferase. Other types of complexation mediate energy transfer to an “antenna protein” altering the color and quantum yield of a bioluminescence reaction. Spatial structures of the complexes reveal an important role of electrostatic forces in governing the corresponding weak interactions and define the nature of the interaction surfaces. The most reliable structural model is available for the protein-protein complex of the Ca²⁺-regulated photoprotein clytin and green-fluorescent protein (GFP) from the jellyfish Clytia gregaria, solved by means of X-ray crystallography, NMR mapping and molecular docking. This provides an example of the potential strategies in studying the transient complexes involved in bioluminescence. It is emphasized that structural studies such as these can provide valuable insight into the detailed mechanism of bioluminescence.     

The molecular basis for protein kinase A anchoring revealed by solution NMR

Compartmentalization of signal transduction enzymes into signaling complexes is an important mechanism to ensure the specificity of intracellular events. Formation of these complexes is mediated by specialized protein motifs that participate in protein-protein interactions. The adenosine 3',5'-cyclic monophosphate (cAMP)-dependent protein kinase (PKA) is localized through interaction of the regulatory (R) subunit dimer with A-kinase-anchoring proteins (AKAPs). We now report the solution structure of the type II PKA R-subunit fragment RIIalpha(1-44), which encompasses both the AKAP-binding and dimerization interfaces. This structure incorporates an X-type four-helix bundle dimerization motif with an extended hydrophobic face that is necessary for high-affinity AKAP binding. NMR data on the complex between RIIalpha(1-44) and an AKAP fragment reveals extensive contacts between the two proteins. Interestingly, this same dimerization motif is present in other signaling molecules, the S100 family. Therefore, the X-type four-helix bundle may represent a conserved fold for protein-protein interactions in signal transduction.     

The role of MukE in assembling a functional MukBEF complex

The MukB-MukE-MukF protein complex is essential for chromosome condensation and segregation in Escherichia coli. The central component of this complex, the MukB protein, is related functionally and structurally to the ubiquitous SMC (structural maintenance of chromosomes) proteins. In a manner similar to SMC, MukB requires the association of two accessory proteins (MukE and MukF) for its function. MukF is a constitutive dimer that bridges the interaction between MukB and MukE. While MukB can condense DNA on its own, it requires MukF and MukE to ensure proper chromosome segregation. Here, we present a novel structure of the E. coli MukE-MukF complex, in which the intricate crystal packing interactions reveal an alternative MukE dimerization interface spanning both N- and C-terminal winged-helix domains of the protein. The structure also unveils additional cross-linking interactions between adjacent MukE-MukF complexes mediated by MukE. A variant of MukE encompassing point mutations on one of these surfaces does not affect assembly of the MukB-MukE-MukF complex and yet cannot restore the temperature sensitivity of the mukE∷kan strain, suggesting that this surface may mediate critical protein-protein interactions between MukB-MukE-MukF complexes. Since the dimerization interface of MukE overlaps with the region of the protein that interacts with MukB in the MukB-MukE-MukF complex, we suggest that competing MukB-MukE and MukE-MukE interactions may regulate the formation of higher-order structures of bacterial condensin.     

Dynamic property is a key determinant for protein-protein interactions

Dynamic property is highly correlated with the biological functions of macromolecules, such as the activity and specificity of enzymes and the allosteric regulation in the signal transduction process. Applications of the dynamic property to protein function researches have been discussed and encouraging progresses have been achieved, for example, in enzyme activity and protein-protein docking studies. However, how the global dynamic property contributes to protein-protein interaction was still unclear. We have studied the dynamic property in protein-protein interactions based on Gaussian Network Model and applied it to classify biological and nonbiological protein-protein complexes in crystal structures. The global motion correlation between residues from the two protomers was found to be remarkably different for biological and nonbiological complexes. This correlation has been used to discriminate biological and nonbiological complexes in crystal and gave a classification rate of 86.9% in the cross-validation test. The innovation of this feature is that it is a global dynamic property which does not rely directly on the interfacial properties of the complex. In addition, the correlation of the global motions was found to be weakly correlated with the dissociation rate constant of protein complexes. We suggest that the dynamic property is a key determinant for protein-protein interaction, which can be used to discriminate native and crystal complexes and potentially be applied in protein-protein dynamic rate constants estimations.     

Efficient comprehensive scoring of docked protein complexes using probabilistic support vector machines

Biological systems and processes rely on a complex network of molecular interactions. While the association of biological macromolecules is a fundamental biochemical phenomenon crucial for the understanding of complex living systems, protein-protein docking methods aim for the computational prediction of protein complexes from individual subunits. Docking algorithms generally produce large numbers of putative protein complexes with only few of these conformations resembling the native complex structure within an acceptable degree of structural similarity. A major challenge in the field of docking is to extract near-native structure(s) out of the large pool of solutions, the so called scoring or ranking problem. A series of structural, chemical, biological and physical properties are used in this work to classify docked protein-protein complexes. These properties include specialized energy functions, evolutionary relationship, class specific residue interface propensities, gap volume, buried surface area, empiric pair potentials on residue and atom level as well as measures for the tightness of fit. Efficient comprehensive scoring functions have been developed using probabilistic Support Vector Machines in combination with this array of properties on the largest currently available protein-protein docking benchmark. The established classifiers are shown to be specific for certain types of protein-protein complexes and are able to detect near-native complex conformations from large sets of decoys with high sensitivity. Using classification probabilities the ranking of near-native structures was drastically improved, leading to a significant enrichment of near-native complex conformations within the top ranks. It could be shown that the developed schemes outperform five other previously published scoring functions.     

Atomic contact vectors in protein-protein recognition

The ability to analyze and compare protein-protein interactions on the structural level is critical to our understanding of various aspects of molecular recognition and the functional interplay of components of biochemical networks. In this study, we introduce atomic contact vectors (ACVs) as an intuitive way to represent the physico-chemical characteristics of a protein-protein interface as well as a way to compare interfaces to each other. We test the utility of ACVs in classification by using them to distinguish between homodimers and crystal contacts. Our results compare favorably with those reported by other authors. We then apply ACVs to mine the PDB for all known protein-protein complexes and separate transient recognition complexes from permanent oligomeric ones. Getting at the basis of this difference is important for our understanding of recognition and we achieved a success rate of 91% for distinguishing these two classes of complexes. Although accessible surface area of the interface is a major discriminating feature, we also show that there are distinct differences in the contact preferences between the two kinds of complexes. Illustrating the superiority of ACVs as a basic comparison measure over a sequence-based approach, we derive a general rule of thumb to determine whether two protein-protein interfaces are redundant. With this method, we arrive at a nonredundant set of 209 recognition complexes--the largest set reported so far.     

Shape complementarity of protein-protein complexes at multiple resolutions

Biological complexes typically exhibit intermolecular interfaces of high shape complementarity. Many computational docking approaches use this surface complementarity as a guide in the search for predicting the structures of protein-protein complexes. Proteins often undergo conformational changes to create a highly complementary interface when associating. These conformational changes are a major cause of failure for automated docking procedures when predicting binding modes between proteins using their unbound conformations. Low resolution surfaces in which high frequency geometric details are omitted have been used to address this problem. These smoothed, or blurred, surfaces are expected to minimize the differences between free and bound structures, especially those that are due to side chain conformations or small backbone deviations. Despite the fact that this approach has been used in many docking protocols, there has yet to be a systematic study of the effects of such surface smoothing on the shape complementarity of the resulting interfaces. Here we investigate this question by computing shape complementarity of a set of 66 protein-protein complexes represented by multiresolution blurred surfaces. Complexed and unbound structures are available for these protein-protein complexes. They are a subset of complexes from a nonredundant docking benchmark selected for rigidity (i.e. the proteins undergo limited conformational changes between their bound and unbound states). In this work, we construct the surfaces by isocontouring a density map obtained by accumulating the densities of Gaussian functions placed at all atom centers of the molecule. The smoothness or resolution is specified by a Gaussian fall-off coefficient, termed "blobbyness." Shape complementarity is quantified using a histogram of the shortest distances between two proteins' surface mesh vertices for both the crystallographic complexes and the complexes built using the protein structures in their unbound conformation. The histograms calculated for the bound complex structures demonstrate that medium resolution smoothing (blobbyness = -0.9) can reproduce about 88% of the shape complementarity of atomic resolution surfaces. Complexes formed from the free component structures show a partial loss of shape complementarity (more overlaps and gaps) with the atomic resolution surfaces. For surfaces smoothed to low resolution (blobbyness = -0.3), we find more consistency of shape complementarity between the complexed and free cases. To further reduce bad contacts without significantly impacting the good contacts we introduce another blurred surface, in which the Gaussian densities of flexible atoms are reduced. From these results we discuss the use of shape complementarity in protein-protein docking.     

Inducing protein-protein interactions with molecular glues

The drugable proteome is limited by the number of functional binding sites that can bind small molecules and respond with a therapeutic effect. Orthosteric and allosteric modulators of enzyme function or receptor signaling are well-established mechanisms of drug action. Drugs that perturb protein-protein interactions have only recently been launched. This approach is more difficult due to the extensive contact surfaces that must be perturbed antagonistically. Compounds that promote novel protein-protein interactions promise to dramatically expand opportunities for therapeutic intervention. This approach is precedented with natural products (rapamycin, FK506, sanglifehrin A), synthetic small molecules (thalidomide and IMiD derivatives) and indisulam analogues.     

Protein docking using a genetic algorithm

A genetic algorithm (GA) for protein-protein docking is described, in which the proteins are represented by dot surfaces calculated using the Connolly program. The GA is used to move the surface of one protein relative to the other to locate the area of greatest surface complementarity between the two. Surface dots are deemed complementary if their normals are opposed, their Connolly shape type is complementary, and their hydrogen bonding or hydrophobic potential is fulfilled. Overlap of the protein interiors is penalized. The GA is tested on 34 large protein-protein complexes where one or both proteins has been crystallized separately. Parameters are established for which 30 of the complexes have at least one near-native solution ranked in the top 100. We have also successfully reassembled a 1,400-residue heptamer based on the top-ranking GA solution obtained when docking two bound subunits.     

Filtering and selection of structural models: combining docking and NMR

It is generally accepted that protein structures are more conserved than protein sequences, and 3D structure determination by computer simulations have become an important necessity in the postgenomic area. Despite major successes no robust, fast, and automated ab initio prediction algorithms for deriving accurate folds of single polypeptide chains or structures of intermolecular complexes exist at present. Here we present a methodology that uses selection and filtering of structural models generated by docking of known substructures such as individual proteins or domains through easily obtainable experimental NMR constraints. In particular, residual dipolar couplings and chemical shift mapping are used. Heuristic inclusion of chemical or biochemical knowledge about point-to-point interactions is combined in our selection strategy with the NMR data and commonly used contact potentials. We demonstrate the approach for the determination of protein-protein complexes using the EIN/HPr complex as an example and for establishing the domain-domain orientation in a chimeric protein, the recently determined hybrid human-Escherichia. coli thioredoxin.     

基于质谱技术的蛋白质互作研究进展

蛋白质作为生命活动的执行者,其功能往往体现在与其他蛋白质的相互作用中,研究蛋白-蛋白相互作用对于人们深入了解和预防传染病、靶向治疗多基因疾病、阐明蛋白质的分子作用机制及各种复杂的生命现象具有重要意义。目前,有多种技术被用来研究蛋白间的相互作用,研究难点在于实时捕获瞬时或弱蛋白质间的相互作用,质谱技术（mass spectrometry, MS）可在某种程度上解决该难点。由于质谱技术可研究简单的蛋白质复合物再到大规模的蛋白质组实验,基于质谱技术研究蛋白质间相互作用被越来越多地应用于科学研究中。综述了蛋白质间相互作用检测方法的研究进展,重点介绍了氢氘交换质谱法和化学交联质谱法研究蛋白质间相互作用的优缺点及其应用,最后对基于质谱技术研究蛋白质间相互作用进行了总结与展望,以期为深入开展相关研究提供借鉴。